MHD Mode Analysis Using the Unevenly Spaced Mirnov Coils in the Keda Torus eXperiment
Bibliographic record
Abstract
Due to the discrete nature of the saddle coils for the active feedback control of the plasma instabilities, the emergence of the sideband modes is inevitable. In the Keda Torus eXperiment (KTX), the edge Mirnov coils are unevenly distributed on the inner surface of the vacuum vessel to suppress the sideband modes. These arrays of the Mirnov coils are used for the feedback control system of KTX. They are also used for the magnetohydrodynamics (MHD) mode identification, which is a fundamental and significant method to distinguish and describe the plasma instabilities. A set of suitable MHD mode analysis methods has been utilized to complete the mode detection, including the spatial discrete Fourier transform (SDFT) method, the singular value decomposition (SVD) method and the Lomb periodogram method. These methods can obtain comprehensive mode information of the plasma instabilities and their results can be used as the feedback of the feedback control system. These methods have been successfully applied to detect and characterize an impulsive mode of (m = 1, n = 0) and rotating modes of (m = 2, 3, 4, n = 1) in the tokamak plasma of KTX, while the matrix decomposition technique is not applicable for KTX.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".